👋 Hi, I’m Martin Orkuma

Data Scientist with an active Secret Clearance and over 4 years of experience turning data into clear insights and actionable strategies for making data-driven solutions.
My work focuses on building reproducible, data-driven pipelines that translate complex datasets into actionable insights.

I am currently pursuing a Master’s degree in Biological Data Science and have experience in statistical modeling, machine learning, and cross-platform analytics workflows.

📫 Connect with me on LinkedIn: https://www.linkedin.com/in/martin-orkuma/

🚀 Technical Toolkit

• Programming & Scripting: Python, R, Bash (WSL/Linux)

• Machine Learning & Analytics: Regression, Classification, Clustering, PCA, Model Evaluation, Cross Validation, TensorFlow, and PyTorch.

• Statistical Methods: Hypothesis Testing, ANOVA, Experimental Design, Inferential Statistics, Longitudinal Data Analysis

• Python: Pandas, NumPy, scikit-learn, scikit-image, Matplotlib, Seaborn, virtual environments (venv)

• Data Management: SQL (Joins, Common Table Expressions, Window Functions), data cleaning and validation

• Data Visualization: Tableau, PowerBI, and Matplotlib.

• Platforms & Tools: Git/GitHub, Jupyter, RStudio, WSL, Azure, Virtual environments

📂Featured Repositories

• Naked Mole-Rat Ovarian Follicle Machine-Learning Project
  End-to-end machine learning pipeline for automated ovarian follicle segmentation and counting in naked mole rat histological images, integrating reproducible preprocessing, annotation, model training, and evaluation workflows.
• Comparative Fetal Overaian Reserve Analysis
  Comparative analysis of fetal ovarian reserve formation across three mammalian species using histological and biological datasets.
• Human Accelerated Regions Comparative Genomic Project
  Human Accelerated Regions (HARs) in Comparative Genomics: Association of Human-Lineage Accelerated Noncoding Regions with Brain Development and Function.
• Alzheimer's Disease Demographic Analysis
  Exploratory and statistical analysis of demographic and clinical factors associated with Alzheimer’s disease diagnosis.
• US Healthcare Data Breach
  End-to-end analysis of U.S. healthcare data breaches, emphasizing data wrangling, temporal trends, and reproducible Bash-driven workflows.

🎯 Interests & Focus Areas

• Computational biology
• Computer vision
• Machine learning
• Population health outcomes